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Record W2159388301 · doi:10.1186/1747-597x-6-34

Difficulty accessing crack pipes and crack pipe sharing among people who use drugs in Vancouver, Canada

2011· article· en· W2159388301 on OpenAlexafffundabout
Lianping Ti, Jane A. Buxton, Evan Wood, Ruth Zhang, Julio Montaner, Thomas Kerr

Bibliographic record

VenueSubstance Abuse Treatment Prevention and Policy · 2011
Typearticle
Languageen
FieldMedicine
TopicHIV, Drug Use, Sexual Risk
Canadian institutionsSt. Paul's HospitalBC Centre for Disease ControlUniversity of British ColumbiaSimon Fraser University
FundersNational Institute on Drug AbuseCanadian Institutes of Health ResearchNational Institutes of Health
KeywordsMedicineOdds ratioConfidence intervalLogistic regressionForensic engineeringEngineeringInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Crack pipe sharing can increase health risks among people who use drugs, yet the reasons for sharing these pipes have not been well described. Therefore, we sought to identify the prevalence and correlates of crack pipe sharing among a community-recruited sample of people who use illicit drugs in Vancouver, a setting where crack pipes are provided at low or no cost. FINDINGS: Data for this study were derived from two prospective cohorts of people who use drugs: the Vancouver Injection Drug Users Study (VIDUS) and the AIDS Care Cohort to evaluate Exposure to Survival Services (ACCESS). Multivariate logistic regression was used to identify factors independently associated with crack pipe sharing. Among 503 crack users, 238 (47.3%) participants reported having shared a crack pipe in the previous six months. Having acquired a mouthpiece in the last six months (adjusted odds ratio [AOR] = 1.91; 95% confidence interval [CI]: 1.31 - 2.79) and difficulty finding new pipes (AOR = 2.19; 95%CI: 1.42 - 3.37) were positively associated with pipe sharing. Binge drug use (AOR = 1.39; 95%CI: 0.96 - 2.02) was marginally associated with sharing pipes. DISCUSSION: There was a high prevalence of crack pipe sharing in a setting where crack pipes are distributed at low or no cost. Difficulty accessing crack pipes was independently and positively associated with this behavior. These findings suggest that additional efforts are needed to discourage crack pipe sharing as well as increase access to crack pipes.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.604
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.045
GPT teacher head0.318
Teacher spread0.273 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations32
Published2011
Admission routes3
Has abstractyes

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